论文标题
音频摘要具有音频功能和概率分布差异
Audio Summarization with Audio Features and Probability Distribution Divergence
论文作者
论文摘要
多媒体来源的自动汇总是一项重要任务，可以通过在维护相关信息的同时凝结来源来促进对个人的理解。在本文中，我们关注基于音频特征和分布差异的概率的音频摘要。我们的方法基于提取性摘要方法，旨在选择最相关的段，直到达到时间阈值。它考虑了该细分市场的长度，位置和信息性价值。通过映射从其MEL频率的Cepstral系数及其相应的Jensen Shannon Divergence得分发出的一组音频功能来获得每个段的信息。通过多重评估器方案的结果表明，我们的方法提供了可理解且内容丰富的摘要。
The automatic summarization of multimedia sources is an important task that facilitates the understanding of an individual by condensing the source while maintaining relevant information. In this paper we focus on audio summarization based on audio features and the probability of distribution divergence. Our method, based on an extractive summarization approach, aims to select the most relevant segments until a time threshold is reached. It takes into account the segment's length, position and informativeness value. Informativeness of each segment is obtained by mapping a set of audio features issued from its Mel-frequency Cepstral Coefficients and their corresponding Jensen-Shannon divergence score. Results over a multi-evaluator scheme shows that our approach provides understandable and informative summaries.
